I was trying to train a model and getting the following error. I am confused why I am getting this error.
And the shape of all the variables are:
Data shape: torch.Size([321, 20, 14])
Mask shape: torch.Size([321, 20])
Decay shape: torch.Size([321, 20])
Redecay shape: torch.Size([321, 20])
The code is given below -
data = T.as_tensor(data.values.astype(float), dtype=T.float32)
data=data.view(int(data.shape[0]/args.seq_len), args.seq_len, data.shape[1])
mask = T.as_tensor(mask.values.astype(float), dtype=T.float32)
mask=mask.view(int(mask.shape[0]/args.seq_len), args.seq_len, mask.shape[1])
decay=mask[:,:,1]
rdecay=mask[:,:,2]
mask=mask[:,:,0]
data=data.squeeze()
mask=mask.squeeze()
decay=decay.squeeze()
rdecay=rdecay.squeeze()
ret_f, ret, disc = run_on_batch(model,discriminator,data,mask,decay,rdecay, args, optimizer=None,optimizer_d=None,epoch=None)
Error message:
IndexError Traceback (most recent call last)
<ipython-input-161-f02c9fd37373> in <module>
3 #oBmi, oBmiF, iBmi, oAge, oSex = run(ARGS)
4
----> 5 run(ARGS)
6
<ipython-input-160-636128776031> in run(args)
26
27 elif args.train:
---> 28 trainLoss,discLoss,gLoss, valLoss,discValLoss,gValLoss = run_epoch(args, model, discriminator)
29 # return trainLoss,discLoss,gLoss, valLoss,discValLoss,gValLoss
30
<ipython-input-159-922ded87c953> in run_epoch(args, model, discriminator)
84
85
---> 86 ret_f, ret, disc = run_on_batch(model,discriminator,data,mask,decay,rdecay, args, optimizer,optimizer_d,epoch)#,bmi_norm)
87 print(ret_f)
88 RLoss=RLoss+ret['loss'].item()
~/Work/deep-learning-based-packet-imputation/BiGAN/biGan/bgan_i_ganOrig.ipynb in run_on_batch(model, discriminator, data, mask, decay, rdecay, args, optimizer, optimizer_d, epoch)
~/.local/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
887 result = self._slow_forward(*input, **kwargs)
888 else:
--> 889 result = self.forward(*input, **kwargs)
890 for hook in itertools.chain(
891 _global_forward_hooks.values(),
~/Work/deep-learning-based-packet-imputation/BiGAN/biGan/bgan_i_ganOrig.ipynb in forward(self, data, mask, decay, rdecay, args)
~/.local/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
887 result = self._slow_forward(*input, **kwargs)
888 else:
--> 889 result = self.forward(*input, **kwargs)
890 for hook in itertools.chain(
891 _global_forward_hooks.values(),
~/Work/deep-learning-based-packet-imputation/BiGAN/biGan/ugan_i_ganOrig.ipynb in forward(self, values, masks, deltas, args, direct)
IndexError: index 20 is out of bounds for dimension 1 with size 20
Thank you for your help.